Thesis (M.A. Sc.)--University of Toronto, 2006. / Source: Masters Abstracts International, Volume: 45-03, page: 1547.

Thesis (Ph. D.)--University of Wisconsin--Madison, 1983. / Typescript. Vita. Description based on print version record. Includes bibliographical references (leaves 186-191).

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Ultracentrifugation and imaging techniques of human blood serum are precise and information-rich methods for obtaining information about an individual’s lipoprotein particle content. The information derived from lipoprotein separations via an ultracentrifuge plays a key role in the area of preventative medicine in regards to atherosclerosis. Two of the most critical lipoprotein characteristics, diameter and density, are well preserved with the proper isopycnic gradient. Currently, lipoprotein particles are stained, ultracentrifuged, and profiled through image analysis. This particular technique is helpful in determining particle density and can be correlated loosely with particle concentration. The need to completely quantify lipoprotein concentrations is imperative in assessing risk factors accurately. Light scattering techniques, primarily Rayleigh scattering, are applied to density separated serum samples in resulting in improved qualitative data with progress in quantitative measurements through imaging alone. The Rayleigh theory dictates that a particle’s scattered intensity is based upon the incident intensity, the particle’s diameter, and the particle’s concentration when strict criteria are met within the sample and imaging apparatus. Applying this innovative imaging technique of Rayleigh scattering to ultracentrifuge tubes containing separated lipoproteins, particle concentrations at differing diameters can be calculated. This thesis primarily goes through the time consuming task of optimizing the innovative Rayleigh scattering system so that correct quantitative estimations can be performed. Constrained by Rayleigh theory and system limitations, lipoproteins of 15 nm to 35 nm are focused upon. By doing so, previously disguised data in regards to lipoprotein subclasses is exposed. Lipoprotein diameters are estimated from Rayleigh imaged serum profiles and the estimations are confirmed through secondary size analysis achieved by dynamic light scattering instrumentation. In addition to Rayleigh optimization, a strategy for quantifying the ultracentrifuged lipoprotein particles using the recently applied scattering technique is explained in detail providing a foundation for further research. In regards to all feasibility studies presented within this thesis, much success was achieved in furthering quantitation efforts in lipoprotein density profiling.

Ultracentrifugation and imaging techniques of human blood serum are precise and information-rich methods for obtaining information about an individual’s lipoprotein particle content. The information derived from lipoprotein separations via an ultracentrifuge plays a key role in the area of preventative medicine in regards to atherosclerosis. Two of the most critical lipoprotein characteristics, diameter and density, are well preserved with the proper isopycnic gradient. Currently, lipoprotein particles are stained, ultracentrifuged, and profiled through image analysis. This particular technique is helpful in determining particle density and can be correlated loosely with particle concentration. The need to completely quantify lipoprotein concentrations is imperative in assessing risk factors accurately. Light scattering techniques, primarily Rayleigh scattering, are applied to density separated serum samples in resulting in improved qualitative data with progress in quantitative measurements through imaging alone. The Rayleigh theory dictates that a particle’s scattered intensity is based upon the incident intensity, the particle’s diameter, and the particle’s concentration when strict criteria are met within the sample and imaging apparatus. Applying this innovative imaging technique of Rayleigh scattering to ultracentrifuge tubes containing separated lipoproteins, particle concentrations at differing diameters can be calculated. This thesis primarily goes through the time consuming task of optimizing the innovative Rayleigh scattering system so that correct quantitative estimations can be performed. Constrained by Rayleigh theory and system limitations, lipoproteins of 15 nm to 35 nm are focused upon. By doing so, previously disguised data in regards to lipoprotein subclasses is exposed. Lipoprotein diameters are estimated from Rayleigh imaged serum profiles and the estimations are confirmed through secondary size analysis achieved by dynamic light scattering instrumentation. In addition to Rayleigh optimization, a strategy for quantifying the ultracentrifuged lipoprotein particles using the recently applied scattering technique is explained in detail providing a foundation for further research. In regards to all feasibility studies presented within this thesis, much success was achieved in furthering quantitation efforts in lipoprotein density profiling.

No description available.

Thesis (Ph. D.)--University of Washington, 2005. / Vita. Includes bibliographical references (leaves 134-145).

No description available.

The filtered Rayleigh scattering (FRS) optical diagnostic has become an attractive technique for advanced aerodynamic measurements. The appeal of FRS is that it can simultaneously quantify density, temperature, and vector velocity. Additionally, it is entirely non-intrusive to the flow since the technique leverages how laser light scatters off of molecules naturally present in the gas. Acquired FRS data considered herein is in the form of a frequency spectrum. To process this data, a measurement model for the FRS spectrum is used, where inputs to this model are the flow field quantities of interest and the output is a representative FRS spectrum. An iterative procedure on these quantities is performed until the model spectrum matches the measured spectrum. However, as observed in certain applications of this technique, there is a range of measurement configurations where the standard methods to model this spectrum do not agree with measured spectra, even at known flow conditions. This disagreement causes large bias uncertainties in determined flow field quantities. This work leverages a data-driven approach to diagnose this disagreement by utilizing an extensive FRS database. Data analysis indicates that the widely used Tenti S6 model for the Rayleigh scattering lineshape is invalid in certain operating regions. A new Rayleigh lineshape modeling methodology, the Cabannes model, is introduced that vastly improves the agreement between measured and modeled FRS signals. Analysis of the Cabannes model indicates that one only needs to use this modeling methodology for FRS and not laser Rayleigh scattering (LRS). This improved measurement model can be used to mitigate bias uncertainties, and, in turn, improve the reliability of the FRS optical instrument. / Doctor of Philosophy / The filtered Rayleigh scattering (FRS) laser-based measurement technique has become an attractive tool for aerodynamic measurements. Leveraging the theory of Rayleigh scattering, measuring how laser light scatters off of air molecules can be used to determine the temperature, density, and velocity of the air. A specific combination of temperature, density, and velocity results in a unique, measured FRS signal. A computational model of this FRS signal is then used to go from FRS signal to those three quantities of interest. However, as observed by certain applications of this technique, there is a certain range of measurement cases where the standard methods to model this signal do not agree with measured signals at known values for temperature, density, and velocity of the air. This disagreement between modeled and measured signals causes large errors, and, therefore, decreases the reliability of this measurement for those cases. This work analyzes an extensive FRS database to determine the source of this disagreement. The conclusion from this data analysis is that the widely used computational model in the community is not correct for certain applications of this FRS measurement. A new method to model FRS signals is proposed in this work, which vastly improves the agreement between measured and modeled signals. This improved computational model can be used to remove the large errors seen in this FRS measurement system that were previously caused by modeling errors. This, in turn, will improve the reliability of this technique across the whole application space of applied aerodynamic measurements.